Research Scientist

Job Description

We are seeking a business-oriented Machine Learning Engineer with strong fundamentals in classical ML and modern AI, including Generative AI. This role focuses on applying AI to real-world business problems, particularly in time series, tabular, and document-based data. The ideal candidate is comfortable working autonomously, collaborating across international teams, and translating complex analytical findings into clear, actionable insights for stakeholders. Key Responsibilities Analyze complex datasets (time series, tabular, numerical, and temporal data) to identify patterns, trends, anomalies, and outliers Design, build, evaluate, and explain ML models aligned to real business use cases Break down ambiguous or complex business problems into solvable ML tasks Interpret model results, analyze errors, and connect outcomes back to business impact Communicate findings clearly to non-technical stakeholders and ask the right follow-up questions Propose and iterate on AI-driven solutions based on data insights Collaborate closely with cross-functional and international teams in English

Skills and Requirements

Strong fundamentals in machine learning concepts Hands-on experience with deep learning / neural networks and modern AI approaches Solid understanding of model evaluation, limitations, and trade-offs Ability to explain models and results in simple, intuitive terms Experience with Explainable AI (XAI) concepts and techniques Strong judgment on when Generative AI adds value—and when it does not Understanding of agentic AI concepts (design-level grasp is sufficient) Data & Use Cases Time series and temporal data analysis Numerical and high-dimensional tabular datasets Anomaly detection, trend modeling, and outlier identification Applying ML outputs directly to business decision-making Programming & Tools Python (practical proficiency; perfection not required) PyTorch (preferred over TensorFlow) scikit-learn, XGBoost, pandas Experience with Python ML libraries in time series and tabular contexts Deployment experience on Azure or a comparable cloud platform To avoid: PySpark, Databricks

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to [email protected].